Method and apparatus for monitoring power transmission

ABSTRACT

An apparatus for measurement of power in an electric power transmission line is disclosed. The apparatus comprises a magnetic field sensor for measuring the magnetic field at the electric power transmission line and transmitting magnetic field data to a processor. The magnetic field sensor is arranged at a minimum threshold distance from the electric power transmission line. The apparatus also has a voltage sensor arranged distally from the magnetic field sensor for transmitting voltage waveform data to the processor and a transfer function calculator for calculating the relationship between the transmitted voltage waveform data at the voltage sensor and transmission line voltage waveform data.

CROSS REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of U.S. patent applicationSer. No. 12/278,672, filed on May 10, 2010, which is a U.S. nationalstage application claiming priority to PCT Application No.PCT/EP2008/061997, which claims the benefit of the filing dates of U.S.Provisional Applications 60/973,046 filed on 17 Sep. 2007 and 60/976,946filed on 2 Oct. 2007.

BACKGROUND OF THE INVENTION Field of the Invention

The present invention relates to an apparatus and method for measurementof power in an electric power transmission line.

Brief Description of the Related Art

The traditional monopolies of electrical utility companies have beenrelaxed in the past few years in the European Union and in the UnitedStates. There has developed as a result a growing market in wholesalefor electric energy. Utility companies, independent power producers, andpower marketers as well as brokers are some of the participants in thevolatile electricity supply market. It is known, for example, thatvariables such as the time of day and date, weather, temperature and oilprices play a role in the pricing of electricity in a given region.Furthermore, the pricing of the electricity is dependant on theoperational status of electric generation and use facilities in thatregion as well as the transmission capacity of an electric powertransmission network. The participants in the electric power marketsrequire access to real-time information as well as historical data onthe operational status of the electric generation and use facilities aswell as the electric power transmission lines in the region. Thisinformation allows the development of trading strategies in electricalpower and responses to power system events (such as disruptions in thepower supply due to failures of transformers).

The relaxation of the monopoly status of traditional electric utilitieshas resulted in increased competition for customers among suppliers ofelectrical energy. Information relating to the use of electrical energyby the potential customers would be extremely useful to those involvedin the bidding for electrical supply contracts. It would also be furtheradvantageous to determine information on the supply and the demand ofthe electrical energy over time without having to directly connect tothe electrical power transmission lines.

Methods and systems for the measurement for the electrical powertransmission are known from several prior art documents. For exampleU.S. Pat. No. 6,714,000 (Staats, assigned to Genscape, Inc.) teaches amethod for the remote monitoring of the magnitude and the direction ofnet electrical power and count flow to or from a facility reducedmonitored over a prolonged period of time. The method described in the'000 patent application” includes the detection and the measurement ofthe magnetic field emanating from the monitored electrical powertransmission lines and detecting a signal which is synchronized to thepower system frequency emanating from the power lines. The methodfurther includes valuation, storing and transmission of the data on theelectromagnetic field that emanates from the electrical powertransmission line.

A further patent application, international patent application No.WO2006/112839 (Genscape Intangible Holding, Inc.) also teaches a methodand a system for the substantially real-time monitoring of theoperational dynamics of power, plants and other components in an ACpower grid. The monitoring is done by using information collected from anetwork of power grid frequency detection and reporting devices. Theinvention allows for the real-time detection and reporting of certainpower grid events, such as a power plant trips or failures.

International patent application No. WO2007/030121 (Genscape IntangibleHolding, Inc.) teaches a system for monitoring the power flow along anelectric power transmission line which includes a plurality of magneticfield monitors placed at selected positions. The system further includesa central processing facility for the communication of the power flow toan end user.

European Patent No. EP1 297 347 (Genscape Intangible Holding, Inc.)discloses an apparatus for remotely measuring and monitoring an electricpower transmission line. The apparatus comprises a first sensor which isresponsive to a first component of a magnetic flex density associated,with the electric power transmission lines and which outputs a voltproportional to the magnetic flex density generated by current flowingthrough set electrical power transmission line. The apparatus furtherincludes a second sensor which outputs a voltage proportional to a netelectrical potential associated with the electrical power transmissionline. The values for the voltage and the current flowing through theelectrical power transmission line are passed to a central processingfacility which combines the phase of the measured electrical potentialwith the phase of the measured magnetic flex density in order todetermine the phase of the electrical potential relative to the magneticflux density and that by determining from the face of the electricalpotential relative to the magnetic flux density. The phase angle of thecurrent flowing through the electrical power transmission line withrespect to the voltage of the transmission line is also determined. Apower factor on the electric power transmission line and the magnitudeand the direction of the power flowing through the electrical powertransmission line is thereby calculated. It should be noted that thevoltage sensor and the, magnetic flux sensor are substantiallyco-located, as can be seen from FIG. 1 of the patent.

Other companies also measure power flowing along transmission lines. Forexample, the Norwegian company powermonitor.org supplies informationabout the German power plants. Their product is described in the article“Slik drives strøm spionasje”, Økonomisk Rapport April 2006, 40-41.Another Norwegian company, Energieinfo AS, Stavern, has filed aNorwegian patent application entitled “Fremgangsmåte og apparat forovervåkning av produksjon og overføring av elektrisk kraft” (ApplicationNo. NO 2007 2653). The contents of this application are, however, notyet public.

SUMMARY OF THE INVENTION

The apparatus and method of the current invention allow the calculationof the magnitude and direction of power flow in substantially real time.The term “real time” in this context means that the calculation iscarried out within a time frame of less than typically 20 milliseconds.

The apparatus and method of the current invention allow the measurementof the power factor—including both active and reactive power and alsoenable the measurement of the deviation of the power factor from theexpected power factor. By “not real-time” or “close to real-time” wenormally mean using measured values within, for example, 5-500 second inan algorithm that is configured to give secondary outputs such as U-1phase angles, reactive power etc.

The apparatus and method of the current invention allow the measurementor the calculation of transfer function of signals in close to real time(i.e. within a time frame of, for example, 5 s to 500 s). Power gridparameters, such as the shape and behavior of the signals as well as theperiod of the signals, the nominal frequency of the signals (forexample, 50 Hz in Europe or 60 Hz in the United States) as well ashigher and lower harmonic frequencies, can also be measured. In oneaspect of the invention, the apparatus and method of the currentinvention furthermore enable the measurement of deviations of thesemeasured power grid parameters relative from the expected power gridparameters.

In one aspect of the invention, a power network database is built. Thepower network database comprised in close to real time power networkdata including the parameters and values of power production, power flowand more generally information about state of the grid. The powernetwork database will also store the power network data for historicalpurposes.

In a further aspect of the invention, power network prediction modelscan be built which, using the power network data and historical data,describe the condition of power generation and power transmission systemand also enable the prediction of the power transmission network'sfuture behavior.

In a further aspect of the invention, state estimators are constructedusing the power network prediction models which can be incorporated withfurther data from the power market, such as weather data, oil reserves,cultural aspects (including TV shows) and weather forecasts. This allowsthe building of a set of scenarios for the power transmission networkwith corresponding probabilities. Information about the scenarios can besold.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 shows an overview of the system;

FIG. 2 shows an overview of the processes and the dataflow in the systemin more detail;

FIG. 3 shows the magnetic field sensor

FIG. 4 shows the voltage phase sensor

FIG. 5 shows the trigger signal from the voltage sensor

FIG. 6 illustrates an example of the determination of power flowdirection

FIG. 7 shows the power flow from Sweden to Norway

FIG. 8 illustrates the determination of the direction of power flow.

DETAILED DESCRIPTION OF THE INVENTION

For a complete understanding of the present invention and the advantagesthereof, reference is now made to the following detailed descriptiontaken in conjunction with the Figures.

It should be appreciated that the various aspects of the inventiondiscussed herein are merely illustrative of the specific ways to makeand use the invention and do not therefore limit the scope of inventionwhen taken into consideration with the claims and the following detaileddescription. It will be further appreciated that features from oneembodiment of the invention may be combined with features from otherembodiments of the invention.

The teachings of the cited documents should be incorporated by referenceinto the description.

FIG. 1 shows an example of the invention. FIG. 1 shows the completesystem 10 for the measurement of power in an electric power transmissionline 20. The electric power transmission line 20 is shown in FIG. 1 as asingle line strung between pylons 25. It will be appreciated that theelectric power transmission line 20 will be generally made up ofmultiple lines. Each of the multiple lines will carry a separate currentand have a magnetic field 35 about the multiple lines. It will also beappreciated that the electric power transmission lines 20 may be laid ona surface or buried underground.

One or more magnetic field sensors 30 are mounted at a distance from theelectric power transmission line 20. The magnetic field sensors 30measure the magnetic field 35 generated by the electric powertransmission line 20. Advantageously the one or more, magnetic filedsensors are arranged close to the base of the pylons 25. This is becausethe electric power transmission line 20 sags between any two of thepylons 35. The sag of the electric power transmission line 20 willincrease in hot weather and also the electric power transmission line 30may move during storms due to wind. The movement and/or sag of theelectric power transmission line 30 will affect the magnetic field 35.If, however, the magnetic field sensors 30 are arranged close to thebase of the pylons 25—at which point the electric power transmissionline 20 is fixed—then the sag and/or movement of the electric powertransmission line 20 will be substantially eliminated.

Typically the magnetic field sensors 30 are placed between 25 and 400 mfrom the electric power transmission lines. The exact coordinates of themagnetic field sensors 30 are measured, for example, using the GlobalPositioning System as this information is needed to identify theelectric power transmission line 20 being measured but also to calculatethe power being, transmitted over the electric power transmission line20 as will be explained later.

It will be further noted that FIG. 1 shows only two of the magneticfield sensors 30 arranged at the bottom of two of the pylons 25 of theelectric power transmission line 20. It will be noted that it is notnecessary to have multiple magnetic field sensors 30 per pylon 25 orelectric power transmission line 20. Generally, there will be onemagnetic field sensor 30 for one single electric power transmission line20, and n or less magnetic field sensors 30 if n electric powertransmission lines 25 are close. By close is meant typically less than 1km. For example if there are two electric power transmission lines 20 at30 m distance (or two electric power transmission lines 20 at the samepylon 25) we can use a single magnetic field sensor 30 (which measuresboth the X and Y magnetic fields and the phase/time). The reason forthis is because the time is measured very accurately, and not only thepeak of the magnetic field signal. By inspecting the phase differencebetween the X and Y magnetically field sensors 30 (inside the samemeasurement unit) we are able to solve the equation for the current oftwo electric power transmission lines 20 if, at the same time, thegeometry of the electric power transmission lines 20 and the placementof the measurement min is known. The measurement is either done in realtime (inside the measurement unit) or one needs to time tag the X and Ymagnetic field measurements very accurately and do the computationafterwards. For calibration of the system and finding the transferfunctions it is possible to use several measurement units at the sameelectric power transmission line 20 for a period of time.

FIG. 1 also shows a processor 40 connected to the plurality of magneticfield sensors 30 by first data lines 33. The first data lines 33transfer in substantially real time magnetic field data 37 representingthe magnetic field 35 measured by the magnetic sensor 30. A voltagesensor 50 is also connected to the processor 40 by second data lines 53.The second data lines 53 transfer in substantially real time voltagephase, data 55 to the processor 40. The voltage sensor 50 is placed tothe low voltage part of the power network. The low voltage part of thepower network is connected through transformers and other lines(represented by reference numeral 45) to the electric power transmissionnetwork 20.

It will be noted that the processor 40 does not need to be situatedclose to the plurality of magnetic field sensors 30. Similarly theprocessor 40 does not need to be situated close to the voltage sensor50. The voltage sensor 50 needs to be connected to the same AC networkas the electric power transmission line 20. In other words, there can beno DC connection between the voltage sensor 50 and the electric powertransmission line 20. In Europe this requirement is met, for example, inthe electric power grid of central Europe (i.e. Germany, Denmark,Netherlands, Belgium, France) and the electric power grid of Scandinavia(Sweden, Norway).

FIG. 1 also shows a clock 38. The clock 38 is highly accurate and isused to send time signals to local clocks at the magnetic field sensors30 and the processor 40. The clock 38 could be the GPS system.

It should be further noted that the processor 40 does not need to besituated in any specific country since the processor 40 can acquire themagnetic field data 37 and/or the voltage waveform data 55 remotely. Itwill be noted that it is possible for the processor 40, the magneticfield sensor 30 and the voltage sensor to be in different countries,

A transform phase calculator 60 is connected to the processor 40.Typically the transform phase calculator 60 will be implemented as asoftware module running on the processor 40, but the transform phasecalculator 60 could also be implemented in hardware (as an ASIC chip) orrun on a second processor (not shown). In one aspect of the inventionthe transform phase calculator 60 and routines and algorithms used bythe transform phase calculator 60 have, access to a look-up table 65implemented as a database. This aspect of the invention will beexplained in more detail later.

The apparatus 10 shown in FIG. 1 is able by use of the magnetic fielddata 37 to determine the direction of the current flowing in theelectric power transmission line 20 as the U-1 phase angle (to beexplained later) and other power grid parameters. The other power gridparameters include, but are not limited to the configuration of thepower grid, capacitive load, HVDC load.

The apparatus 10 is able to monitor and evaluate frequencies in theelectric power transmission line 20. The frequencies include not onlythe nominal frequency (50 Hz in Europe; 60 Hz in US) but also higher andlower frequencies as and when required.

It will be recognized that the first data line 33 and the second dataline 53 do not have to be physical cables or other fixed lines. Thefirst data line 33 and the second data line 53 could also be constructedfrom the General Packet Radio Service (GPRS) over the GSM mobilecommunications network. Alternatively the first data line 33 and thesecond data line 53 could be implemented over the UMTS/3G mobilecommunications network, RF, satellite etc. The, mobile communicationsnetwork is shown in FIG. 2. It is preferred to use fixed lines as theuse of the mobile communications network requires significant amount ofpower for the establishment of upstream data channels and/or downstreamdata channels as short intervals of data relating to the magnetic fielddata 37 and the voltage waveform data 55 will need to be established andtransferred across the mobile communications network. In one aspect ofthe invention the magnetic field data 37 and/or the voltage waveformdata 55 is not sent in real-time to the processor 40. Instead themagnetic field data 37 and/or the voltage waveform data 55 istemporarily stored and transmitted in bursts of data packets across themobile communications network. This procedure is to increase, the timebetween each data transfer and thus reduce the rate of establishment ofconnections.

In a further aspect of the invention a prediction algorithm is used tofurther reduce the amount of the magnetic field data 37 and/or thevoltage waveform data 55. The prediction algorithm uses statistical andtrend analysis of the magnetic field data 37 and/or the voltage waveformdata 55 to predict the next values of the magnetic field data 37 and/orthe voltage phase data 55. The same prediction algorithm is incorporatedinto the magnetic field sensor 30, (and the voltage phase sensor 50) andthe processor 40. It will, of course, be appreciated that the predictionalgorithm for the magnetic field data 37 will differ from the predictionalgorithm for the voltage waveform data 55. The magnetic field sensor 30and/or the voltage sensor 50 will then only need to transmit themagnetic field data 37 and/or the voltage waveform data 55 when themeasured next values depart from the predicted next values generatedfrom the prediction algorithm. This substantially saves data transferand also reduces the rate of establishments of connections.

An analogy with vocal data transmission can serve to illustrate thispoint in more detail. Suppose Olga is a transmitter and Peter is areceiver and that Olga's task is to shout, numbers to Peter. Olga needsto shout to Peter each time she wants to send numbers. Olga wants toshout as little as possible and so she writes down the numbers on a notebefore she sends the complete note to Peter. But Peter wants to get thenumbers immediately and does not wait for the note. Normally the numbersare of the series “1, 2, 3, 2, 1, 2, 3, 2, 1 . . . .” If, after Peterreceived the numbers 1, 2, 3 he does not get any more numbers from Olga,he continues to predict the numbers 2, 1, 2, 3, 2, 1, 2, 3 . . . basedon the previous pattern of data that he has already received. Olga knowsthat Peter will do this, and it suits her because it obviates the needfor her to shout each number. This stratagem works fine so long as shesees that the numbers she needs to send follow the series 1, 2, 3, 2, 1,2, 3, 2, 1 . . . . Suddenly Olga sees that she needs to send a 4 andthis number does not match the number predicted by her algorithm. Shethen shouts to Peter “Hello Peter, your algorithm is predicting wrongly.I will send you my note with the correct numbers!”

The apparatus 10 of the invention allows the determination ofconfiguration of the power grid and conditions of the power gridrelative to limits. Thus the apparatus 10 will provide information aboutthe situation concerning the power production and power grid, and canalso compare this information with respect to expected conditions. Thedetermination of the power grid can be particularly useful to anindependent power provider who does not have access to informationrelating to the structure of the power grid (which is held by theoperator of the power grid).

The processor 40 can use the information gained from the magnetic fieldsensors 30 and the voltage sensor 50 to simulate the actions ofproducers of electric power, operators of the power grid and consumers.This provides information which can allow suitable action to be taken tomatch demand for electric power with the availability of electric power.For example, if there is lack of electric power in Italy, a generatingstation in Spain may be manually called in to add to capacity of theelectric power on the power grid capacity. The apparatus 10 can evaluateor predict that such an action has already been done or—using available,historical data—will be done by the generation station in Spain.

In one advantageous aspect of the invention, the processor 40 cansimulate and determine the probability for development of differentscenarios and different modes of operation of the power grid. This canbe done by, for example using State Estimators and Monte Carlo methods.

In one advantageous aspect of the invention, the processor 40 can usesubstantially real-time data together with historical data (stored in adatabase) in the simulations. The processor 40 can evaluate how thesesimulations may impact on the operation of the power grid and theprobability of entering into changed modes of operation. In addition tothe magnetic field data 37 and the voltage waveform data 55 thesimulations can include historic data such as weather data, networkconfiguration data, time-related data, energy price, energy reserves.These simulations can provide probabilities for the power production andthe power grid to identify scenarios different from;expected behavior.

In a further aspect of the invention, multiple magnetically sensorsspread out are used in the same area. The magnetically sensors couldeither be mounted inside the same measurement unit or it can be severalmeasurement units. By then very accurate connect a time measurement toeach magnetically measurement for each magnetically sensor one canafterwards compare the phase and the magnitude of each of themeasurements. By this one can perform calculations to find eitherunknown geometry of the lines and/or measure multiple lines withadditive magnetically fields.

In a further aspect of the invention, a reference generator can beincorporated which can be either fully or partly in phase with noise inthe magnetic field sensor 30 and induced in the magnetic field sensor 30by the electric power transmission line 20. The source of the noise, canbe, for example, from the electric field surrounding the electric powertransmission line 20. The magnetic field sensor 30 calculates the powerand the direction of the, power in the power transmission line 20 usingthe measured magnetic field and the reference generator.

The principles behind the invention will now be explained. It is knownpower (P) is the product of voltage (V) and current (I), i.e.;

P=V*I   Eqn (1)

Therefore any approach to the measurement of electrical power flowingthrough an electrical power transmission line 20 must be based on thedirect measurement of or derivation of current I and the voltage Vflowing through the electrical power transmission line 20. The sign ofthe product of the voltage U and the current I gives the sign of thepower P. For time periods of less than a half cycle (i.e. <10 ms at 50Hz) Eqn (1) is approximately valid both for DC and AC power.

The current I is measured in the invention using the magnetic fieldsensors 30 disposed along the electrical power transmission line 20. Themagnetic field sensors 30 measure the magnetic field 35 associated withthe electrical power transmission line 20. The current I through theelectrical power transmission line 20 can then be calculated inaccordance with Ampere's Law and the Biot-Savart law. Standard vectorcalculus, 1D, 2D or 3D with one or several orthogonal sensors can beused if several lines in the electrical power transmission linecontribute to the magnetic field 35 or if the lines do not have an onedimensional shape (for example due to sagging, as discussed above).

If the voltage V and the current I were always in phase with each otherin the electrical power transmission line 20, then the scalar product ofmeasured RMS voltage and measured RMS current would always indicate theinstantaneous power in the electrical power transmission line 20.

However, in AC power systems, the voltage V and the current I are notexactly in phase, owing to the fact that loads may be reactive ratherthan resistive. This is due to the inductance and capacitance of thecomponents (lines, cables, transformers etc.) making up the grid. Thisgives rise to the power factor being less than unity and therefore thephase difference between the voltage V and the current I must bedetermined in order to obtain an accurate computation of the power. Thedifference in phases between the voltage V and the current I isparticularly noticeable at low electrical power flows and when faultsoccur in the power grid. The phase difference between the voltage V andthe current I will also be significant for a time. The phase differencewill end up at 180° when the power changes direction.

FIG. 2 shows a more detailed overview of the processor 40 according tothe current invention. FIG. 2 shows the magnetic field sensors 30located close to the electric power transmission lines 20. The magneticfield sensors 30 are connected to each other or to a mobile data accessinterface 36 via radio or through the mobile communications network (as,discussed above). The wireless magnetic field sensors (30) may also beconnected to a wireless LAN transceiver 34. The mobile data accessinterface 36 and the LAN transceiver 34 are connected to the processor40 through the Internet.

The processor 40 comprises an authentication check 200 which isconnected to the mobile data access interface 36 and the wireless LANtransceiver 34 to authenticate the data received at the processor. Theauthentication check 200 is also connected to the voltage sensor 50. Itshould be noted that there may be more than one voltage sensor 50 whichmay be placed in the same facility as the processor 40. The data fromthe magnetic field sensors 30 and the voltage sensor 50 is processed inthe raw data storage processor 210 before being stored in the raw datadatabases 220.

A field description database 240 contains a set of data which describe agiven configuration of the power grid. For example, a data set numbercould describe the configuration of the Scandinavian power grid in whicheach of fields in the data set describes the given configuration of eachof the individual parts of the power grid, for example a closed breaker.The field description database 240 includes, but is not limited to dataconcerning breakers, a capacitor coupled to the power grid, theconnections of the electric power transmission lines 20, the length ofthe electric power transmission lines 20, transformers etc. Anotherdataset could be exactly the same as the first data set except that oneof the breakers has a different state, for, example open. Part of thedatasets and the data in the field description database 240 are obtainedfrom public information or by manually inspecting the power grid. Therest of the dataset will mainly be calculated manually by inspecting themeasured values or calculated automatically in accordance with thisinvention.

The processor 40 continuously monitors the data in the system andcalculates the configuration of the power grid at a given time. By suchmeans, it is possible for the processor 40 to determine the givenconfiguration for the power grid at a given time and to use the fielddescription database 240 as a look-up table for input in a gridconfiguration process 260. Let, us take an example. Suppose that theprocessor 40 detects a rapid change in the U×I phase angle from 15degree to 2 degree within 60 s. The processor 40 will then inspect thecurrent data set in the field description database 240 and in so doingdeter mine that this change of the U×I phase angle is typically (or canonly be) because one of the breakers changed from a closed state to anopen state. An additional capacitive load made the power grid morereactive (which leads to a reduced phase angle). The grid configurationprocessor 260 will then update the current state in the fielddescription database 240 to fit the new configuration of the power grid.

If there is a new configuration in the power grid which does not, matchany of the existing states in the field description database 260, thegrid configuration processor 260 will either try to define a new stateand inform an operator or the grid configuration processor 260 willissue an alert and ask for assistance from an operator.

A statistics and probability database 270 continuously maintainsstatistics and determines probabilities for the state of the power grid.One example would be the expected power flow to a given consumer at agiven day and time. For example, in a given one of the electric powertransmission lines 20 at a given time, the probability for a power flowof 60-100 MW might be determined as 68%, the probability of a power flowgreater than 160 MW as 22%, and the probability of a power flow greaterthan 120 MW as 32% etc.

An economic features database 280 contains information related toindirect parameters which can influence the states and actions of thepower grid. These indirect parameters include, history real-time andfuture parameters such as weather forecast, fuel prices, water value,etc.

An estimator module 290 obtains the current state from the fielddescription database 240, obtains statistics and probabilities from thestatistics and probability database 270 and the economical featuresdatabase 280 and constructs new possible grid states with an estimatedprobability. The new possible grid states are, for example, stored in adatabases mirror database 295.

In addition there are a number of processes and databases that monitorthe entire system and perform quality control, SMS handling, VPNsecurity, calibration etc.

FIG. 3 shows an example of the magnetic field sensor 30 which comprisesa sensing coil 310 connected to an amplifier 315 and then to ananalog-digital converter 320. As discussed above, the magnetic fieldsensor 310 measures the magnetic flux in the field close to the electricpower transmission lines 20 in real-time and is typically placed 25-400m away from the electric power transmission line 20. The magnetic fieldsensor 20 is typically configured to measure at suitable time intervals,but also if needed may be configured to measure the change of the fluxof the magnetic field continuously. The measurements taken of themagnetic field may be the bottom-peak value, the integral, the shape,the frequency etc. The magnetic field sensor 30 comprises one or moremagnetic sensor that typically include the search coils 310. In. FIG. 3only one search coil 310 is shown, but this is not limiting of theinvention. The search coil 310 outputs a voltage signal, almostproportional to the change per time in the magnetic flux. It should benoted that other types of magnetic sensors can be used. The A/Dconverter 320 converts the measured voltage values from the search coils310 to digital values.

The magnetic field sensor 30 further includes, a microprocessor 330which processes the digital values from the A/D converter 320 and aglobal positioning and time unit 340 which measures the exact positionof the magnetic field sensor 30, usually using the UPS system and alsothe time. The magnetic field sensor 30 typically includes a GSM module350 for transmitting the data to the processor 40. As discussed above,the GSM module 350 could be replaced by other data transmission devices.

The magnetic field sensor 30 has an exact known position in space. Thisposition is calculated using the global positioning and time unit 340 orcould be done using trigonometric measurements. The global positioningand time unit 340 with the microprocessor 330 is able to very accuratelytag all of the measurements with the given time at the given place ofthe magnetic field sensor 30. In combination with the overall globalposition and timing system it is therefore possible for the processor 40to treat all of the magnetic field sensors 30 in the system as a singlecomposite unit which virtually operates in real-time.

Let us take an example. Consider a 50 ms long snapshot of the currentsignal over the whole power grid taken at the same time. The electricpower transmission lines 20 surrounding the magnetic field sensors havean exact known position in space. This known position can be either berelative to the magnetic field sensors 30, it can be obtained fromofficial information such as maps etc., or from measurements made usingmobile GPS units, etc. Using this known position it is possible to makea mathematical model of the magnetic field at which the magnetic fieldsensor 30 is placed and to set up equations describing how the magneticfield is dependent on the current in the electrical power transmissionlines 20. Basic linear algebra, for example, can be used to solve theseequations.

Global Grid Position and Timing system (GGPT) units are placed in all ofthe measurement units such as the magnetic field sensors 30, theprocessor 40 and the voltage sensor 50 and provide accurate time datafor all parts of the system. The GGPT units are represented on FIG. 1 asthe clock 38. The GGPT units allow spatial data to be computed based ongeometry and the variation of signal speed with time. The GGPT system issimilar to the well-known Global Positioning System (GPS). The GGPTsystem is based mainly on one or several of the known timing systems.These timing systems include, but are not limited to, US GPS satellites,the forthcoming Galileo European Satellites, very accurate RF timingsignals, cellular mobile phones RF signals, accurate local real timeclocks and local accurate geometry measurements. The GGPT system and theGGPT units have an accuracy and resolution typically down tonano-seconds and less than one meter in time and space. The accuracyserves as the basis for evaluating the transfer of a given power signalon the power grid from one location to another location. In a furtheraspect of the invention the time is measured as the point at which thevoltage signal crosses the average voltage value.

The nominal power signal on the power grid has a nominal frequency of 50Hz in Europe and 60 Hz in the US. The nominal power signal has asubstantially sinusoidal form. In theory it would not be possible toextract one period from another in a perfectly linear network. But dueto imperfections in the power grid, there, are variations in frequency(of approx a few hundred mHz) and the power signal has an imperfectsinusoidal form due to disturbances from power producers, the power griditself and consumers. This will lead to overlying frequencies (forexample harmonics) of the nominal frequency. These unique mixed signals,naturally self-generated on the power grid, can then be handled as inputand output in a network analyser.

The function of the voltage sensor 50 is to measure the phase of thevoltage signal. As discussed above, the voltage sensor 50 is typicallylocated in an office, near a centralized computer or at a position wherethere is very low noise on the voltage signal. FIG. 4 shows a schematicdiagram of the voltage sensor 50 according to one embodiment of theinvention.

The voltage sensor 50 includes a comparator 440. One input of thecomparator 430 is connected between a voltage divider formed fromresistances 410 and 420. One input of the resistance 410 is connected adomestic power outlet (typically 220V AC in Europe) 400. One input ofthe resistance 420 is connected to ground 430. It will be noted that thedomestic power outlet 400 can be several hundreds of kilometers from thepower grid in which the power flow is calculated. This is feasible aslong as a transfer function between the locations of the power grid andthe location of the voltage sensor 50 is known or can be calculated.

The other input of the comparator 440 is set to a fixed and very stablethreshold voltage, V_(ref) at 450 which close to 0 volt. An output 460of the comparator 440 will typically go high when the input from thevoltage divider is equal or larger than the threshold voltage V_(ref) at450. The actual magnitude of the fixed threshold voltage V_(ref) is notimportant and may be unknown, but the fixed threshold voltage V_(ref)must be very stable, over time. Optionally, the threshold voltage couldbe given as the average of the maximum and minimum of the peak voltagemeasured at the domestic power outlet 400. The comparator 440 has a typeof hysteresis so the output 460 is given only when the input voltagefrom the voltage divider goes from negative to positive. In analternative aspect of the invention, the hysteresis is not needed.However, it has been discovered that if no hysteresis is used it willslightly complicate the operation of the voltage sensor 50 and thesubsequent calculations in the GGPT. The duration of the high output at460 from the comparator 440 does not need to be known. The durationshould be sufficiently high, e.g. higher than 100 μS so to allow amicrocontroller for example to use the start of the ramp of the outputof the comparator as an input. The comparator 440 is typically turned onevery time a trigger is to be used by the GGPT, e.g. example every 10 s.

In a further aspect of the invention, the time is measured as the pointat which the voltage signal crosses the average voltage value.

FIG. 5 below compares graphically an input signal for the GGPT (IN) andthe trigger signal (TR) generated from the, comparator 440.

The calculation of the U-I phase angle by use of the GGPT will now beexplained. Suppose it is required to calculate the U-I phase angle at agiven location on the power grid. The common way to calculate the U-Iphase angle is to subtract the time difference between the sinusoidalcurrent waveform I and the sinusoidal voltage waveform U where they bothcross the time axis and then transform the time difference to anequivalent phase difference in radians based on the known time period.

The magnetic field sensor 30 tag all of the measurements of thesinusoidal current waveform I with exact times relative to the GGPTsystem at a first location. At, or at almost (for example ±5 s) the sametime, the voltage sensor 50 gives an exact time for the sinusoidalvoltage waveform somewhere else relative to the GGPT system at a secondlocation. By the use of lookup tables for the transfer function of thevoltage from the first location to the second location, it is possibleto calculate the timing of the voltage waveform U at the same place andtime as the first location at which the current measurement was done.This then allows the matching of the period of the current waveform Iand the period of the voltage waveform U at a given place and time.

The voltage sensor 50 can output a pulse and time tag for every period(i.e. every 1/50th second in Europe or 1/60th second in the USA) or atintervals of several seconds. To avoid too large a quantity of data inthe database, the voltage sensor 50 does not normally output a time tagfor every period of the voltage waveform U. If the voltage sensor 50does not output a time tag for each period, the time must be adjusted tofit the given period measured by the magnetic field sensor 30.Specifically, the adjustment is needed to extrapolate the elapsed timeperiod owing to slight fluctuations of the actual time period relativeto the nominal time period of the power grid caused by frequencyfluctuations.

The correction time is given by the Equation:

n·time_period·adjustment

where n is the number of period mismatches between the two measurementsat the first location and the second location, time_period is thenominal time period of the power grid and is given by 1/f where f is theAC supply frequency (typically 50 Hz or 60 Hz) and adjustment is anadjustment value derived from an adjustment table. This adjustment tableis continuously being built up by the voltage sensor 50 which normallymake measurements in shorter periods than the magnetic field sensors.

This adjustment table will typically include several records. Forexample, the adjustment table can have a record with a field n and afield adjust. In the initial record, the field n can, for example, havethe value 45678 and adjust the value 20.001 which indicates that thetime period was 1 μs longer than nominal time period at the time of therecording of the initial record. 25 periods later another record iscreated and the value of n=45703. The adjust value is 20.0015 whichindicates a period time 1.5 μs longer than the nominal time_period.Similarly at a further 25 periods the value of n=45728 and the adjustvalues is 20.002—indicating a period time 2 μs longer. If the magneticfield sensors carry out the measurement of a period which is 55 periodsafter the initial record and the voltage sensor 50 performs themeasurement 50 periods after the initial record (i.e. at the secondrecord above) we can now interpolate from the adjustment table the deltat the peak of the voltage waveform which will have changed over the 5periods at which the to measurements made by the magnetic field sensors30.

It will, of course, be noted that if the voltage sensor 50 and themagnetic field sensors 30 perform the measurements at the same periodthis adjustment will not be needed.

The lookup tables for the transfer function stored in the fielddescription database 240 are predefined and pre calculated continuouslymainly by the configuration module 260.

The GGPT is able to generate an electrical pulse at the same relativetime all over the power grid, or at least a pulse which is afterwardspossible to calculate backwards to give a relative, time tag all overthe power grid. An example of a time pulse from the GGPT is shown inFIG. 5 IN. The time difference Δ_(tV) can be measured between the rampof the time pulse (IN) generated by the GGPT and the ramp of thecomparator output 460 shown as TR in FIG. 5. As an example in FIG. 5Δ_(tV) !Here we need to put in the right notation for underscore v,either mms or ttms! is approximately 23 ms. The time transfer functionfor a voltage signal in the power grid at the given grid configurationhas previously been determined to be U_(t trans)(condition,x,y,z) and inthis case is stored in the lookup tables in the field descriptiondatabase 240 and is found to be 12 ms. One example of this can be thepropagation time from a given place in Spain to a given place in Poland.By now adjusting for the calibration of the system and taking intoaccount the adjusted transfer function this will give us the unknownphase time U(t,x,y,z) of the voltage at any known place at any locationon the power grid.

Let us take as an example at a location A having the co-ordinate (x,y,z)where a given magnetic field sensor 30 is located, the current at themagnetic field sensor 30 at the location A (x,y,z) will have the sametime difference Δ_(tI) relative to the time pulse from the GGPT. So theU×I phase at which the magnetic field sensor 30 is located will be givenby:

U×I Phase(condition,t,x,yJz)=(Δ_(tV)−(Δ_(tI) +n·time_period·adjustment_(u))−U _(t_trans)(condition,x,y,z)*2π/T

where T is the time period of the AC supply.

Another way to find the direction of the power and power factor will nowbe described. In this example, the power factors and the direction ofthe power can also be determined by signal analysis. The magnetic fieldsensor 30 analyzes the shape of the measured alternating current signal.Ideally, the shape of the measured alternating current signal is a sinuswith a fixed time period T (T= 1/50 s in Europe or T= 1/60 s in US). Inpractice, the power grid's alternating current sinusoidal waveform hasdeviations from a perfect sinusoid waveform. This may be, for example,due to inaccuracy in power production, devices installed in the powergrid (for example HVDC), resistive, inductive, capacitive loads, andnoise from the consumers (e.g. high frequency switching consumers). Asan example a transformer station with a high grade of saturation (e.g.at maximum throughput) will cause harmonic frequencies superimposed onthe nominal sinusoidal waveform both on the input currents and on theoutput currents. These harmonics may be of a frequency in the range1000-2000 Hz, for example, and will overlay and deviate the sinus of themeasured alternating current signal at nominal frequency.

FIG. 7 shows two examples of a 50 Hz sinusoidal waveform withsuperimposed higher frequencies. The term “sinus-noise” will be used forthese deviations from the ideally preferred shape. Some of thissinus-noise will be related to the voltage, some of the sinus-noiserelated to the current and some of the sinus-noise related to the U×Iphase angle. For the main part of the sinus-noise there will be acorrelation of the contribution to voltage noise, current noise and U×Iphase angle noise at the same time. Using the magnetic field sensors 30it is only possible to inspect the sinus-noise related to the current,so the focus is on the sinus-noise seen on the current signal. Owing tothe physical relation between the current sinus-noise and the U×I phaseangle it is then possible to determine the U×I phase angle indirectlyfrom the sinus-noise in the current signal. It is hence possible todetermine from the U×I phase angle the direction of the power and thereactive power.

FIG. 6 illustrates a computation done on an electrical powertransmission line to determine the direction of the power. FIG. 6 showsa pair of sinusoidal power sources 600 and 620 which supply power toconsumers 610 and 630. To illustrate the problem we have introduced a“black box” whey we measure inside without any information from outside.If we measure the alternating current in a black box 640 at a middlepoint 650 we shall see the charge carriers moving in one half of thecycle from point 660 to point 670. In the other half of the cycle frompoint 670 to point 670—ideally in the form of a sinusoidal waveform. Ifpreviously we know the RMS voltage of the circuit then this will enableus to calculate the amount of power, but not the direction or the activepart. It will not be possible to determine whether the power is flowingtowards the point 660 or towards the point 620.

Almost all circuits have some kind of asymmetry. This will be also trueat the middle point 650 of the circuit of FIG. 6. By carefullyinspecting the current signature of the alternating current signal inthe circuit, one will normally see that the alternating current signaldoes not have a perfect sinusoidal waveform as described above. Thealternating current signal will be normally asymmetric. This asymmetricdeformation of the sinusoidal waveform will normally be changed or justmirrored when the power direction changes, using this information we areable to know when the power direction changes.

Consider FIGS. 7 and 8 which show examples of two measurements of theelectric power transmission line 20 from Norway to Sweden. The firstmeasurement denoted by “serie1” is done when there is a flow of powerfrom Norway to Sweden. The second measurement denoted by “serie2” isdone about 1 hour later when there is a flow of power from Sweden toNorway. By carefully matching the graphs by mirroring them and makingappropriate adjustment one can clearly see that the shape issubstantially identical. The appropriate adjustment can be, by way ofexample, to multiply by a factor k and/or to shift the graph in the timedomain.

This is shown in FIG. 8. As can be seen, the curve “Serie2” in FIG. 7(where the power flow is in the opposite direction of curve Serie1 1hour earlier) is now scaled by a factor k and “mirrored” to fit thecurve “Serie1”. The curve “Serie3” is the same as the curve “Serie2”,but, just shifted in time in order to fit to the curve “Serie1”. Bydoing this we see that we can get a better match of the twomeasurements, and further conclude that the power has changed direction.If the power had not changed direction in the two measurements we shouldsee that the curve Serie1 and the curve Serie2 in FIG. 7 would matchbetter than the curve Serie1 and the curve Serie2 curves in the FIG. 8.

This simple example and analysis shows it is possible to determine thechange in the power direction without knowing or measuring the voltagein the circuit.

This can be done mathematically inside the measurement unit 30 or in theprocessor 40 by storing a set of digitized values of one period of thesinusoidal waveform of the alternating current signal I to give a set ofvalues I₁. The set of digitized values is mirrored to give a set ofmirrored digitized values, I_(m1). An error value E₁ is calculated bycomparing the set of digitized values I₁ with the set of mirroreddigitized values I_(m1). Subsequently a new set of digitized values ofthe sinusoidal waveform, I₂ is stored and a new error value E₂ iscalculated by comparing the new set of digitized values I₂ with itsmirror image.

If E₂ is less than E₁ then the power has changed direction.

As mentioned above, a physical cause of this sinus-noise can be atransformer which is close to saturation. Due to the saturation, thevoltage in the transformer will then be, distorted by superimposedharmonics. There is a physical relation between the voltage and thecurrent in the electric power transmission lines 20 coupled to the inputand output windings of the transformer, so that the harmonics will alsobe superimposed on the sinusoidal waveform of the alternating currentsignal. The harmonics will not follow the U×I phase angle of the nominalfrequency, but will vary slightly for example due to different impactfrom the reactance and capacitive load.

By even more detailed analysis of the shape it is also possible todetermine the U×I phase angle, the capacitive/inductive load, theconfiguration of the power grid, as well as other parameters thatcharacterize the power production, the grid and the consumer etc.

This analysis and information can either be used in real time inside themagnetic field sensor 30 or the information can be transferred to theprocessor 40, where the information can be further analyzed incombination with other information from the power grid.

An example calculation of the transfer function will now be explained. Atransfer function is typically given by the formula:

Excitation→“Transfer function”→Response.

The excitation is normally measured by the magnetic field sensor 30 inthe invention. This excitation will be the nominal periodic alternatingcurrent (50 or 60 Hz) with sinus-noise (as explained above). It isimpossible to detect and distinguish two different sinusoidal periodsfrom each other, but the superimposed noise can be detected andrecognized as a unique signal. Consequently, the sinus-noise on thepower grid is the alternating current signal seen and this alternatingcurrent signal can be handled as the excitation. The power grid willhave a given transfer function at a given time at a given condition ofthe power grid. The transfer function will depend on the currentflowing, the temperature, the configuration of the circuit breakers onthe power grid etc.

The response is typically the sinus-noise measured, with anothermagnetic field sensor 30 or by measurements of the propagation time of acurrent signal to the voltage sensor 50.

To get a full understanding and description of the power grid it isnecessary to set up an equation or a lookup table that represents or isthe transfer function. By making the above described measurements of theexcitations and response we can then solve for the unknown transferfunction This can be done for example by use of standard networkanalysis and synthesis method, e.g. by transfer to the frequency domain,Laplace transforms etc.

To solve for the unknown transfer function we may also utilize otherphysical equations and known relations for example the formula for speedof a signal in a power line.

The transfer function estimated is used as the Ut_trans(condition,x,y,z)which was used above to find the U×I phase angle and the direction ofthe power flow. This is the transfer function of the voltage signal onthe power grid and will make it possible to find the U×I phase angle allover the power grid without measuring the magnitude of the voltage. Forexample, by placing one of the voltage sensors 50 in an office in Swedenand another one of the voltage sensors 50 in an office in Norway one canget information about some parts of the voltage transfer function fromSweden to Norway. There is a relation between the current and thevoltage in the electric power transmission line 20 and by placingseveral ones of the magnetic field sensors 30 on the electric powertransmission line 20 between Sweden and Norway one will get informationabout the transfer function for signals in the current.

In an alternative aspect of the invention, a measurement of the magneticflux using a magnetic flux sensor close to the electrical powertransmission line 20 is carried out in a conventional manner. Thisallows the current magnitude through the electrical power transmissionline 20 to be determined. However, in this case, the voltage phase isdetermined by detecting noise that is induced by the electrical voltageacross the electrical power transmission line 20. This may be donelocally to the electrical power transmission line 20 by measuringelectrical noise induced in the flux sensor itself, or alternatively itmay be done remote from the electrical power transmission line 20 usinga modified Global Grid Position and Timing System (GGPT) that isinstalled remote from the electrical power transmission line 20.Regardless of where the actual voltage phase measurement is made, asignal generator is provided that generates a reference signal whoseperiod can be tuned using one or more filters. The signal generator maybe installed within the magnetic flux sensor or GGPT according towhether local or remote measurement is performed. For example, thesignal generator may be coupled locally by cable or via an RFconnection. The signal generator may also be coupled remotely via theInternet or GPRS.

Filters in the signal generator may be adjusted to pick up signals fromthe measured magnetic flux sensing circuits. The filters can also betuned to pick up either environmental noise or noise induced in themagnetic flux sensor or GGPT depending on whether local measurement orremote measurement is done.

The typical noise that may be picked up by the filter is noise from theelectronic components in the magnetic flux sensor or GGPT or noise fromthe environment such as the electrical field from the electrical powertransmission line 20. It may normally be assumed that the typical noisewill include some flux components induced by the power grid in whichcase the U×I phase angle may be calculated by using the measuredmagnetic flux for the current I and the reference generator for thevoltage U.

In a further embodiment of the invention, a measurement station isinstalled close, or proximate, to the electric power transmission line20 and measures the magnetic flux. At a given time provided by theGlobal Grid Position and Timing System (GGPT) the measurement stationstarts to count the number of sinusoidal periods which elapse (normallyabout 1/50 s in Europe or 1/60 s in USA). A voltage period counter unit(VPGU) is connected to the low voltage section of the power grid andcounts the voltage periods on the low voltage grid. The VPCU is similarto the voltage sensor 50 described above with particular reference toFIG. 1. At a given time which is the same as the time provided to themeasurement station by the GGPT the VPCU starts to count the number ofperiods which, elapse. The measurement station and the VPCU transmittheir data to a local server. The local server compares the two valuesof elapsed periods as received respectively from the measurement stationand the VPCU and calculates the phase angle U×I.

The numbers of elapsed periods from the measurement station or the VPCUdo not need to be integers, but can be decimals representing fractionalperiods that have elapsed during the measurement interval. Using themeasured flux and a predetermined magnitude of grid voltage as provided,for example, by the electricity supplier, it is possible to calculateboth the current I and the voltage U. By use of the calculated phaseangle, it is possible to calculate the active, the reactive and thedirection of the power.

The grid configuration module 260 shown in FIG. 2 continuously monitorsthe data in the system and calculates the instantaneous gridconfiguration at a given time. The grid configuration module 260 willmainly inspect the transfer functions of the power grid. If the transferfunction changes, the grid configuration module 260 will evaluate ifthere is a new configuration of the power grid. If the gridconfiguration module 260 evaluates that there has been a change in thegrid configuration, the grid configuration module 260 will update to anew power grid state in the field description database 240.

As an example, the transfer function of the power grid will changeimmediately if two switches on the power grid at different places inlocation change mode.

The main reason for not measuring the magnitude of the voltage by thevoltage sensor 50, but the phase, is because the transfer function forthe magnitude of the voltage is too inaccurate to be used for the powercalculation. Even if one placed a voltage sensor 50 proximate to theelectric power transmission line the magnitude will cause voltagepotential and phase errors owing to variations in the environment. Inthe invention, this error is avoided since the invention uses apredefined RMS value for the voltage stored in the field descriptiondatabase 240 and finds the voltage phase in an controlled environment(i.e. remote from the electric power transmission line) with lessvariations. This predefined RMS value for the voltage is typicallydetermined from a priori knowledge as disclosed by the electricitysupply company. In other words, if the nominal voltage of the powertransmission line is 420 kV, then the voltage is assumed to be 420 kV.The value for the voltage can also be determined by one-time use ofhighly accurate and expensive electrical field sensors.

The data calculation module 250 calculates the current in a givenelectric power transmission line in the power grid from the raw database220 and the field description database 240. The data calculation module250 also uses the transfer function and computes the phase relationbetween the current I and the voltage U. This is done as describedabove. The calculation need not be done in real time, but can beperformed off-line with a delay anywhere between a few seconds toseveral days after the measurements were made. Normally the magneticfield sensor 30 and the voltage sensor 50 do not make a measurement atthe same time. As a result, the data calculation module 250 searches forthe values that are closest in time relative to the measurement made bythe magnetic field sensors 30, and uses this in combination with themeasured period time/frequency to interpolate values that fit as best aspossible with the values of the magnetic field sensors 30. Once this isdone, the data calculation module 250 calculates the effective power,the reactive power, the resistive power, loss at different places in thepower grid etc. and updates the value database 255. The data calculationmodule 250 does not necessary need to operate using a single sequentialprocess, but may effect several sub processes, which can be located atdifferent places in time and space.

As mentioned above, the measurements of the voltage U and the current Iwill typically not be done in the same place and time (in real-time),but will normally be done during different cycles of the alternatingcurrent. Consequently, there will normally be a need to interpolatebackwards in order to estimate the same signal for both the voltage Uand the current I both in space and time. To make this possible and tofind the transfer function within the required accuracy, the magneticfield sensors 30, the voltage sensor 50, the raw database 220, the fielddescription database 240 and the data calculation module 250 also needto keep track of accuracy at any time for the given values as thefrequency(t), the derivative(t) of the values, the accuracy of themeasurements (e.g. 51+−0.01% Hz), the deviation from, normal +1 Hz,example the slope of the increase of the measurement/time (e.g. 0.002Hz/s) etc. The system is adapted to evaluate values and either replacethem with, estimated values or give warnings if the values are outsidegiven acceptable limits.

Since the magnetic field sensors 30 are normally solar/battery powered,it is desirable to use as little power as possible in the magnetic fieldsensor 30. Normally the measurements which are done in intervals will besent in data packets from time to time. To reduce the size of the data,packets, algorithms can be used to compress the data. In addition thedata packets will be temporarily stored (or never sent) if the measuredchanges from measurement to measurement are within certain limits. Inthis way the size of the data packets can possible be increased, butthere will be less data packets to send. The average power consumptionover a time period (example 24 h) is normally much more closely relatedto the number of packets transmitted separately than the size of thedata packets. In other words the power consumed is mainly related to thenumber of connections the transmitters establish with the receiver.

In addition to more standards methods to reduce the number of data sizeand data packets as mentioned above, the magnetic field sensor 30 has adata prediction, module as described earlier that reduces the number ofupstream and downstream data packet transfers. This makes the datatransport more efficient and reduces the power consumptionsignificantly.

The invention has been described with respect to the measurement of themagnetic field at the electric power transmission line and the voltagewaveform at a distance. It will be appreciated that it would be possibleto measure the voltage at the electric power transmission line and thecurrent at a distance or any combination of current and/or voltage datain order to obtain the transfer function. Furthermore, it is possible tomeasure the current and/or voltage at more than one point.

Reference Numerals Names 10 Apparatus 20 Electric Power TransmissionLine 25 Pylons 30 Magnetic Field Sensor 33 First Datalines 34 WirelessLAN Transceiver 35 Magnetic field 36 Mobile Data Access Interface 37Magnetic Field Data 38 Clock 40 Processor 45 Network 50 Voltage Sensor53 Second data lines 55 Voltage waveform data 60 Transform waveformcalculator 65 Look-up Table 200 Authentification Check 210 Rasw DataStorage Processor 220 Raw Database 230 Predict Data Processor 240 FieldDescription Database 250 Data calculcation module 255 Value Database 260Grid Configuration Module 270 Statistics and probability database 280Economic Feature Database 290 Estimator Module 295 Database mirrorsdatabase 310 Searching coil 315 Amplifier 320 A/D Converter 330Microprocessor 340 Global Positioning and Time Unit 350 GSM Module 400Domestic Power Outlet 410 Resistance 420 Resistance 430 Ground 440Comparator 450 Reference voltage 460 Output 600 Sinusoidal Power Source610 Consumer 620 Sinusoidal Power Source 630 Consumer 640 Black Box 650Middle Point 660 Point 670 Point

What is claimed is:
 1. An apparatus for measurement of power in anelectric power transmission line comprising: a first electromagneticsensor for measuring the electromagnetic field at the electric powertransmission line and transmitting electromagnetic data to a processor,wherein the first electromagnetic sensor is arranged proximate to but ata distance from the electric power transmission line; a secondelectromagnetic sensor arranged distally from the first electromagneticsensor for transmitting second electromagnetic data to the processor; aclock; and a transfer function calculator for calculating therelationship between the first electromagnetic data and the secondelectromagnetic data.